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Cited by 214

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Network Theory of Organization: A Multilevel Approach

Moliterno, Thomas P., Mahony, Douglas M.·2011·Journal of Management

Abstract

Management research regularly considers social networks and their effects on a wide range of organizational phenomena. Scholars employing the social network perspective have generated a considerable body of organizational research, with much of this scholarship single-level in its focus: exploring how networks of individuals, groups, or firms relate to organizational outcomes at the same level of analysis. However, given that organizations are multilevel systems, a network theory of the organization should, by definition, be multilevel in its scope, considering how networks at one level of the organizational system influence networks at higher and/or lower levels. In this article, the authors overlay canonical multilevel theory on the social network perspective to derive postulates defining the broad theoretical domain of a multilevel network theory of organization. The link between these two theoretical perspectives is the graph theoretical notion of systems of nested networks, allowing the authors to examine how an observed network structure at one level of the system of organizational networks relates to network structures and effects at higher or lower levels of the system.

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Metadata

Authors
Moliterno, T. P., & Mahony, D. M.
Venue
Journal of Management
Published
2010-07-21
Volume
37
Issue
2
Pages
443-467
ISSN
  • 0149-2063 (ISSN-L)
  • 1557-1211
OpenAlex
W1977629085
Cited by
214
References
9
FWCI
21.41
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Network Theory of Organization: A Multilevel Approach. https://app.cochat.ai/papers/10.1177/0149206310371692
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Moliterno, T. P., & Mahony, D. M. (2011). Network Theory of Organization: A Multilevel Approach. Journal of Management. https://doi.org/10.1177/0149206310371692

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.